Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
DeepSeek V4 Pro
71
Gemini 2.5 Pro
65
Verified leaderboard positions: DeepSeek V4 Pro #22 · Gemini 2.5 Pro unranked
Pick DeepSeek V4 Pro if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if coding is the priority.
Coding
+5.0 difference
Knowledge
+8.6 difference
DeepSeek V4 Pro
Gemini 2.5 Pro
$1.74 / $3.48
$1.25 / $10
N/A
117 t/s
N/A
21.19s
1M
1M
Pick DeepSeek V4 Pro if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if coding is the priority.
DeepSeek V4 Pro is clearly ahead on the provisional aggregate, 71 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V4 Pro's sharpest advantage is in knowledge, where it averages 49.4 against 40.8. The single biggest benchmark swing on the page is HLE, 7.7% to 18.8%. Gemini 2.5 Pro does hit back in coding, so the answer changes if that is the part of the workload you care about most.
Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $10.00 output per 1M tokens, versus $1.74 input / $3.48 output per 1M tokens for DeepSeek V4 Pro. That is roughly 2.9x on output cost alone.
DeepSeek V4 Pro is ahead on BenchLM's provisional leaderboard, 71 to 65. The biggest single separator in this matchup is HLE, where the scores are 7.7% and 18.8%.
DeepSeek V4 Pro has the edge for knowledge tasks in this comparison, averaging 49.4 versus 40.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Gemini 2.5 Pro has the edge for coding in this comparison, averaging 63.8 versus 58.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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